Computer supported collaborative learning using CLARE: the approach and experimental findings

  • Authors:

  • Dadong Wan;Philip M. Johnson

  • Affiliations:

  • Center for Information Technology & Management, Walter A. Haas School of Business, University of California, Berkeley, CA;Department of Information and Computer Sciences, University of Hawaii, Honolulu, HI

  • Venue:
  • CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
  • Year:
  • 1994

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Abstract

Current collaborative learning systems focus on maximizing shared information. However, “meaningful learning” is not simply information sharing but, more importantly, knowledge construction. CLARE is a computer-supported learning environment that facilitates meaningful learning through collaborative knowledge construction. CLARE provides a semi-formal representation language called RESRA and an explicit process model called SECAI. Experimental evaluation through 300 hours of classroom usage indicates that CLARE does support meaningful learning, and that a major bottleneck to computer-mediated knowledge construction is summarization. Lessons learned through the design and evaluation of CLARE provide new insights into both collaborative learning systems and collaborative learning theories.